OpenRaiser/Intern-Atlas huggingface dataset:
targetDP: an Abstraction of Lattice Based Parallelism with Portable Performance
Venue: arXiv cs.DC 2014
Year: 2014

To achieve high performance on modern computers, it is vital to map algorithmic parallelism to that inherent in the hardware. From an application developer's perspective, it is also important that code can be maintained in a portable manner across a range of hardware. Here we present targetDP (target Data Parallel), a lightweight programming layer that allows the abstraction of data parallelism for applications that employ structured grids. A single source code may be used to target both thread level parallelism (TLP) and instruction level parallelism (ILP) on either SIMD multi-core CPUs or GPU-accelerated platforms. targetDP is implemented via standard C preprocessor macros and library functions, can be added to existing applications incrementally, and can be combined with higher-level paradigms such as MPI. We present CPU and GPU performance results for a benchmark taken from the lattice Boltzmann application that motivated this work. These demonstrate not only performance portability, but also the optimisation resulting from the intelligent exposure of ILP.
Performance Estimation of 2*3 MIMO-MC-CDMA using Convolution Code
Venue: arXiv cs.IT 2014
Year: 2014

In this paper we estimate the performance of 2by3 MIMOMCCDMA system using convolution code in MATLAB which highly reduces BER by increasing the efficiency of system. MIMO and MCCDMA system combination is used to reduce bit error rate and also for forming a new system called MCCDMA which is multi user and multiple access schemes used to increase the performance of the system. MCCDMA system is a narrowband flat fading in nature which converts frequency selective to numerous narrowband flat fading multiple parallel sub-carriers to increase the efficiency of the system. Now this MCCDMA system can also be enhanced by grouping with 2by3 MIMO system which utilizes ZF decoder at the receiver to decrease BER in which half rate convolutionally encoded Alamouti STBC block code is used for channel encoding scheme as transmit diversity of MIMO with multiple transmit antenna. And convolution encoder is also used as source encoder or FEC encoder in MIMOMCCDMA. Advantage of using MIMO-MC-CDMA using convolution code is due to reduce complexity of system and also for reducing BER and finally to increase gain of system. Now after this we examine system in various modulation techniques like, 8PSK, 16QAM, QPSK, 32QAM, 8QAM and 64QAM using MATLAB in Rayleigh fading channel.
NDTAODV: Neighbor Defense Technique for Ad Hoc On-Demand Distance Vector(AODV) to mitigate flood attack in MANETS
Venue: arXiv cs.NI 2014
Year: 2014

Mobile Ad Hoc Networks (MANETs) are collections of mobile nodes that can communicate with one another using multihop wireless links. MANETs are often deployed in the environments, where there is no fixed infrastructure and centralized management. The nodes of mobile ad hoc networks are susceptible to compromise. In such a scenario, designing an efficient, reliable and secure routing protocol has been a major challengesue over the last many years. The routing protocol Ad hoc On-demand Distance Vector (AODV) has no security measures in-built in it. It is vulnerable to many types of routing attacks. The flood attack is one of them. In this paper, we propose a simple and effective technique to secure Ad hoc Ondemand Distance Vector (AODV) routing protocol against flood attacks. To deal with a flood attack, we have proposed Neighbor Defense Technique for Ad hoc On-demand Distance Vector (NDTAODV). This makes AODV more robust. The proposed technique has been designed to isolate the flood attacker with the use of timers, peak value and hello alarm technique. We have simulated our work in Network Simulator NS-2.33 (NS-2) with different pause times by way of different number of malicious nodes. We have compared the performance of NDTAODV with the AODV in normal situation as well as in the presence of malicious attacks. We have considered Packet Delivery Fraction (PDF), Average Throughput (AT) and Normalized Routing Load (NRL) for comparing the performance of NDTAODV and AODV.
Faster Reductions for Straight Skeletons to Motorcycle Graphs
Venue: arXiv cs.CG 2014
Year: 2014

We give an algorithm that reduces the straight skeleton to the motorcycle graph in $O(n\log n)$ time for simple polygons and $O(n(\log n)\log m)$ time for a planar straight line graph (PSLG) with $m$ connected components. This improves on the previous best of $O(n(\log n)\log r)$ for polygons with $r$ reflex vertices (possibly with holes) and $O(n^2\log n)$ for general planar straight line graphs. This allows us to speed up the straight skeleton algorithm for polygons and PSLGs. For a polygon with $h$ holes and $r$ reflex vertices we achieve a speedup from $O(n(\log n)\log r + r^{4/3+ε})$ time to $O(n(\log n)\log h + r^{4/3 + ε})$ time in the non-degenerate case and from $O(n(\log n)\log r + r^{17/11 + ε})$ to $O(n(\log n)\log h + r^{17/11 + ε})$ in degenerate cases. For a PSLG with $m$ connected components and $r$ reflex vertices, we gain a speed up from $O(n^{1 + ε} + n^{8/11 + ε}r^{9/11+ε})$ to $O(n(\log n)\log m + r^{4/3 + ε})$ in the non-degenerate case and from $O(n^{1 + ε} + n^{8/11 + ε}r^{9/11+ε})$ to $O(n(\log n)\log m + r^{17/11 + ε})$ in the degenerate case.
Traversing News with Ant Colony Optimisation and Negative Pheromones
Venue: arXiv cs.IR 2014
Year: 2014

The past decade has seen the rapid development of the online newsroom. News published online are the main outlet of news surpassing traditional printed newspapers. This poses challenges to the production and to the consumption of those news. With those many sources of information available it is important to find ways to cluster and organise the documents if one wants to understand this new system. A novel bio inspired approach to the problem of traversing the news is presented. It finds Hamiltonian cycles over documents published by the newspaper The Guardian. A Second Order Swarm Intelligence algorithm based on Ant Colony Optimisation was developed that uses a negative pheromone to mark unrewarding paths with a "no-entry" signal. This approach follows recent findings of negative pheromone usage in real ants.
Design of A Scalable Hybrid MAC Protocol for Heterogeneous M2M Networks
Venue: arXiv cs.NI 2014
Year: 2014

A robust and resilient Medium Access Control (MAC) protocol is crucial for numerous machine-type devices to concurrently access the channel in a Machine-to-Machine (M2M) network. Simplex (reservation or contention based) MAC protocols are studied in most literatures which may not be able to provide a scalable solution for M2M networks with large number of heterogeneous devices. In this paper, a scalable hybrid MAC protocol, which consists of a contention period and a transmission period, is designed for heterogeneous M2M networks. In this protocol, different devices with pre-set priorities (hierarchical contending probabilities) firstly contend the transmission opportunities following the convention based $p$-persistent CSMA mechanism. Only the successful devices will be assigned a time slot for transmission following the reservation based TDMA mechanism. If the devices failed in contention at previous frame, to ensure the fairness among all devices, their contending priorities will be raised by increasing their contending probabilities at the next frame. To balance the tradeoff between the contention and transmission period in each frame, an optimization problem is formulated to maximize the channel utility by finding the key design parameters: the contention duration, initial contending probability and the incremental indicator. Analytical and simulation results demonstrate the effectiveness of the proposed Hybrid MAC protocol.
HEPGAME and the Simplification of Expressions
Venue: arXiv cs.AI 2014
Year: 2014

Advances in high energy physics have created the need to increase computational capacity. Project HEPGAME was composed to address this challenge. One of the issues is that numerical integration of expressions of current interest have millions of terms and takes weeks to compute. We have investigated ways to simplify these expressions, using Horner schemes and common subexpression elimination. Our approach applies MCTS, a search procedure that has been successful in AI. We use it to find near-optimal Horner schemes. Although MCTS finds better solutions, this approach gives rise to two further challenges. (1) MCTS (with UCT) introduces a constant, $C_p$ that governs the balance between exploration and exploitation. This constant has to be tuned manually. (2) There should be more guided exploration at the bottom of the tree, since the current approach reduces the quality of the solution towards the end of the expression. We investigate NMCS (Nested Monte Carlo Search) to address both issues, but find that NMCS is computationally unfeasible for our problem. Then, we modify the MCTS formula by introducing a dynamic exploration-exploitation parameter $T$ that decreases linearly with the iteration number. Consequently, we provide a performance analysis. We observe that a variable $C_p$ solves our domain: it yields more exploration at the bottom and as a result the tuning problem has been simplified. The region in $C_p$ for which good values are found is increased by more than a tenfold. This result encourages us to continue our research to solve other prominent problems in High Energy Physics.
Research at UNIS - The University Centre in Svalbard. A bibliometric study
Venue: arXiv cs.DL 2014
Year: 2014

The scientific output 1994-2014 of the University Centre in Svalbard (UNIS) was bibliometrically analysed. It was found that the majority of the papers have been published as international cooperations and rank above world average. Analysis of the content of the papers reveals that UNIS works and publishes in a wide variety of scientific topics.
Results for grundy number of the complement of bipartite graphs
Venue: arXiv cs.DM 2014
Year: 2014

A Grundy k-coloring of a graph G, is a vertex k-coloring of G such that for each two colors i and j with i < j, every vertex of G colored by j has a neighbor with color i. The Grundy chromatic number (G), is the largest integer k for which there exists a Grundy k-coloring for G. In this note we first give an interpretation of (G) in terms of the total graph of G, when G is the complement of a bipartite graph. Then we prove that determining the Grundy number of the complement of bipartite graphs is an NP-Complete problem
Review of Linpack and Cloudsim on VMM
Venue: arXiv cs.DC 2014
Year: 2014

Virtualization is a framework of dividing the resources of a computer into multiple execution environments which offers a lot of benefits including flexibility, security, ease to configuration and reduction of cost but at the same time it also brings a certain degree of performance overhead. Furthermore, Virtual Machine Monitor (VMM) is the core component of virtual machine (VM) system and its effectiveness greatly impacts the performance of the whole system. This review paper will try to describe the basic knowledge about various virtual machine monitors such as VMware and VirtualBox. It also discussed and explores the benchmark LINPACK and CloudSim available for cloud computing. This benchmark and CloudSim can be used to measure the performance of two different virtual machine monitors in terms of processing speed, time, bandwidth, quality and response of the cloud computing network.
@I to @Me: An Anatomy of Username Changing Behavior on Twitter
Venue: arXiv cs.SI 2014
Year: 2014

An identity of a user on an online social network (OSN) is defined by her profile, content and network attributes. OSNs allow users to change their online attributes with time, to reflect changes in their real-life. Temporal changes in users' content and network attributes have been well studied in literature, however little research has explored temporal changes in profile attributes of online users. This work makes the first attempt to study changes to a unique profile attribute of a user - username and on a popular OSN which allows users to change usernames multiple times - Twitter. We collect, monitor and analyze 8.7 million Twitter users at macroscopic level and 10,000 users at microscopic level to understand username changing behavior. We find that around 10% of monitored Twitter users opt to change usernames for possible reasons such as space gain, followers gain, and username promotion. Few users switch back to any of their past usernames, however prefer recently dropped usernames to switch back to. Users who change usernames are more active and popular than users who don't. In-degree, activity and account creation year of users are weakly correlated with their frequency of username change. We believe that past usernames of a user and their associated benefits inferred from the past, can help Twitter to suggest its users a set of suitable usernames to change to. Past usernames may also help in other applications such as searching and linking multiple OSN accounts of a user and correlating multiple Twitter profiles to a single user.
Continuous Compressed Sensing With a Single or Multiple Measurement Vectors
Venue: arXiv cs.IT 2014
Year: 2014

We consider the problem of recovering a single or multiple frequency-sparse signals, which share the same frequency components, from a subset of regularly spaced samples. The problem is referred to as continuous compressed sensing (CCS) in which the frequencies can take any values in the normalized domain [0,1). In this paper, a link between CCS and low rank matrix completion (LRMC) is established based on an $\ell_0$-pseudo-norm-like formulation, and theoretical guarantees for exact recovery are analyzed. Practically efficient algorithms are proposed based on the link and convex and nonconvex relaxations, and validated via numerical simulations.
Inferring gender of a Twitter user using celebrities it follows
Venue: arXiv cs.IR 2014
Year: 2014

This paper addresses the task of user gender classification in social media, with an application to Twitter. The approach automatically predicts gender by leveraging observable information such as the tweet behavior, linguistic content of the user's Twitter feed and the celebrities followed by the user. This paper first evaluates linguistic content based features using LIWC dictionary and popular neighborhood features using Wikipedia and Freebase. Then augments both features which yielded a significant increase in the accuracy for gender prediction. Results show that rich linguistic features combined with popular neighborhood prove valuables and promising for additional user classification needs.
Modeling Multi-mode D2D Communications in LTE
Venue: arXiv cs.NI 2014
Year: 2014

In this work we propose a roadmap towards the analytical understanding of Device-to-Device (D2D) communications in LTE-A networks. Various D2D solutions have been proposed, which include inband and outband D2D transmission modes, each of which exhibits different pros and cons in terms of complexity, interference, and spectral efficiency achieved. We go beyond traditional mode optimization and mode-selection schemes. Specifically, we formulate a general problem for the joint per-user mode selection, connection activation and resource scheduling of connections.
Understanding the spreading power of all nodes in a network: a continuous-time perspective
Venue: arXiv cs.SI 2014
Year: 2014

Centrality measures such as the degree, k-shell, or eigenvalue centrality can identify a network's most influential nodes, but are rarely usefully accurate in quantifying the spreading power of the vast majority of nodes which are not highly influential. The spreading power of all network nodes is better explained by considering, from a continuous-time epidemiological perspective, the distribution of the force of infection each node generates. The resulting metric, the \textit{expected force}, accurately quantifies node spreading power under all primary epidemiological models across a wide range of archetypical human contact networks. When node power is low, influence is a function of neighbor degree. As power increases, a node's own degree becomes more important. The strength of this relationship is modulated by network structure, being more pronounced in narrow, dense networks typical of social networking and weakening in broader, looser association networks such as the Internet. The expected force can be computed independently for individual nodes, making it applicable for networks whose adjacency matrix is dynamic, not well specified, or overwhelmingly large.
Proximal Reinforcement Learning: A New Theory of Sequential Decision Making in Primal-Dual Spaces
Venue: arXiv cs.LG 2014
Year: 2014

In this paper, we set forth a new vision of reinforcement learning developed by us over the past few years, one that yields mathematically rigorous solutions to longstanding important questions that have remained unresolved: (i) how to design reliable, convergent, and robust reinforcement learning algorithms (ii) how to guarantee that reinforcement learning satisfies pre-specified "safety" guarantees, and remains in a stable region of the parameter space (iii) how to design "off-policy" temporal difference learning algorithms in a reliable and stable manner, and finally (iv) how to integrate the study of reinforcement learning into the rich theory of stochastic optimization. In this paper, we provide detailed answers to all these questions using the powerful framework of proximal operators. The key idea that emerges is the use of primal dual spaces connected through the use of a Legendre transform. This allows temporal difference updates to occur in dual spaces, allowing a variety of important technical advantages. The Legendre transform elegantly generalizes past algorithms for solving reinforcement learning problems, such as natural gradient methods, which we show relate closely to the previously unconnected framework of mirror descent methods. Equally importantly, proximal operator theory enables the systematic development of operator splitting methods that show how to safely and reliably decompose complex products of gradients that occur in recent variants of gradient-based temporal difference learning. This key technical innovation makes it possible to finally design "true" stochastic gradient methods for reinforcement learning. Finally, Legendre transforms enable a variety of other benefits, including modeling sparsity and domain geometry. Our work builds extensively on recent work on the convergence of saddle-point algorithms, and on the theory of monotone operators.
Research On Permanent Magnet BLDC for small electric vehicle
Venue: arXiv cs.SY 2014
Year: 2014

In this paper, different electric motors are studied and compared to see the benefits of each motor and the one that is more suitable to be used in the electric vehicle applications. There are five main electric motor types, DC, induction, permanent magnet synchronous, switched reluctance and brush-less DC motors are studied.
Kevoree Modeling Framework (KMF): Efficient modeling techniques for runtime use
Venue: arXiv cs.SE 2014
Year: 2014

The creation of Domain Specific Languages(DSL) counts as one of the main goals in the field of Model-Driven Software Engineering (MDSE). The main purpose of these DSLs is to facilitate the manipulation of domain specific concepts, by providing developers with specific tools for their domain of expertise. A natural approach to create DSLs is to reuse existing modeling standards and tools. In this area, the Eclipse Modeling Framework (EMF) has rapidly become the defacto standard in the MDSE for building Domain Specific Languages (DSL) and tools based on generative techniques. However, the use of EMF generated tools in domains like Internet of Things (IoT), Cloud Computing or Models@Runtime reaches several limitations. In this paper, we identify several properties the generated tools must comply with to be usable in other domains than desktop-based software systems. We then challenge EMF on these properties and describe our approach to overcome the limitations. Our approach, implemented in the Kevoree Modeling Framework (KMF), is finally evaluated according to the identified properties and compared to EMF.
A Measurement Framework for Directed Networks
Venue: arXiv cs.SI 2014
Year: 2014

Partially-observed network data collected by link-tracing based sampling methods is often being studied to obtain the characteristics of a large complex network. However, little attention has been paid to sampling from directed networks such as WWW and Peer-to-Peer networks. In this paper, we propose a novel two-step (sampling/estimation) framework to measure nodal characteristics which can be defined by an average target function in an arbitrary directed network. To this end, we propose a personalized PageRank-based algorithm to visit and sample nodes. This algorithm only uses already visited nodes as local information without any prior knowledge about the latent structure of the network. Moreover, we introduce a new estimator based on the approximate importance sampling to estimate average target functions. The proposed estimator utilizes calculated PageRank value of each sampled node as an approximation for the exact visiting probability. To the best of our knowledge, this is the first study on correcting the bias of a sampling method by re-weighting of measured values that considers the effect of approximation of visiting probabilities. Comprehensive theoretical and empirical analysis of the estimator demonstrate that it is asymptotically unbiased even in situations where stationary distribution of PageRank is poorly approximated.
On the design of an expert help system for computer algebra systems
Venue: arXiv cs.SC 2014
Year: 2014

It is our intention here only to discuss the nature, complexity and tools concerning the design of Smart Help, an expert help facility for aiding users of Computer Algebra Systems. Although the expert help system presented here has been particularly oriented to REDUCE (as a consequence of our former experience with this system), we point out that the concept of Smart Help can be extended to other Computer Algebra Systems. Technically, Smart Help is a Production System on the top of a particular implementation of MANTRA, a hybrid knowledge representation system, which has REDUCE integrated as an additional knowledge representation module. Since the heuristic level of MANTRA has not yet been implemented, being presently represented by the Lisp language itself, Smart Help is coded in Lisp and resides in the same Lisp session of MANTRA. A prototype of Smart Help is now running on a SUN work-station on an experimental basis.